MongoDB Crash Course | Complete Guide

MongoDB is a NoSQL database widely used in modern applications. It’s fast, flexible, and schema-less, which means you don’t need fixed tables like in SQL databases. Data is stored in documents (JSON-like objects) inside collections (similar to tables), which are part of databases.

I. MongoDB Installation & Setup

1. Install MongoDB – Use the Community Edition from MongoDB’s official site.

2. Open Mongo Shell (mongo sh) – Run queries interactively.

mongo sh

Think of databases as big cabinets, collections as folders, and documents as profile sheets inside folders.

II. Core Concepts

• Document – JSON-like object: {name: "Aarav", age: 25}

• Collection – Group of documents, like a table called users

• Database – Contains collections, like schoolDB

• Schema-less – Each document can have different fields

III. Creating Data (C in CRUD)

MongoDB allows creating documents using insertOne and insertMany.

// Insert single user
db.users.insertOne({name: "Aarav"})

// Insert user with multiple fields
db.users.insertOne({
  name: "Priya",
  age: 22,
  address: {street: "MG Road", city: "Bangalore"},
  hobbies: ["dancing", "painting"]
})

// Insert multiple users at once
db.users.insertMany([
  {name: "Rohit", age: 30},
  {name: "Ananya", age: 28},
  {name: "Karan", age: 24},
  {name: "Sneha", age: 26}
])

Each document is like a profile sheet, and collections group these sheets together.

IV. Reading Data (R in CRUD)

1. Basic Queries

db.users.find() // Get all users
db.users.find().limit(2) // Only first 2 users
db.users.find().skip(1).limit(2) // Skip 1, get next 2
db.users.find().sort({name: 1}) // Sort A-Z
db.users.find().sort({name: -1}) // Sort Z-A
db.users.findOne({age: 22}) // Get first match with age 22
db.users.countDocuments({age: {$lte: 30}}) // Count users age ≤ 30

find() shows all the documents that match a given condition.

2. Filtering Queries

Example:

db.users.find({$or: [{age: {$lte: 25}}, {name: "Rohit"}]})

These operators help filter the documents to match the conditions you want.

3. Projection (Selecting Specific Fields)

db.users.find({name: "Priya"}, {name:1, age:1, _id:0}) // Show only name & age
db.users.find({name: "Priya"}, {age:0}) // Show everything except age
db.users.find({}, {name:1, hobbies:1}) // Show name and hobbies for all users

Projection lets you select only the fields you want to see.

V. Updating Data (U in CRUD)

// Update one user
db.users.updateOne({name: "Aarav"}, {$set: {age: 26}})

// Update multiple users
db.users.updateMany({age: {$gte: 25}}, {$inc: {age: 1}}) // Add 1 year

// Rename field
db.users.updateOne({name: "Priya"}, {$rename: {name: "firstName"}})

// Remove a field
db.users.updateOne({name: "Rohit"}, {$unset: {hobbies: ""}})

// Add to array
db.users.updateOne({name: "Ananya"}, {$push: {hobbies: "singing"}})

// Remove from array
db.users.updateOne({name: "Ananya"}, {$pull: {hobbies: "singing"}})

// Replace whole document
db.users.replaceOne({name: "Karan"}, {name: "Karan", age: 25, city: "Delhi"})

Updating is like editing a profile sheet to change, add, or remove details.

VI. Deleting Data (D in CRUD)

// Delete one user
db.users.deleteOne({name: "Rohit"})

// Delete multiple users
db.users.deleteMany({age: {$exists: false}})

Deleting removes unwanted documents from the collection.

VII. Aggregation (Advanced Queries)

// Count users per age
db.users.aggregate([
  {$group: {_id: "$age", total: {$sum: 1}}}
])

// Average age
db.users.aggregate([
  {$group: {_id: null, avgAge: {$avg: "$age"}}}
])

Aggregation is used to summarize or analyze data across multiple documents.

VIII. Summary

MongoDB is:

• Flexible & fast – Great for apps with dynamic data

• Schema-less – Easy to start without defining tables

• JavaScript-friendly – Commands use JSON-style objects

• Powerful – Supports CRUD operations, filtering, projections, updates, deletions, and aggregation

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